Driving communications in a secure storage network based on data element transitions

1 . A method for generating an optimization indicator based on data state transitions of data elements associated with one or more digital profiles in a secure storage network, the method comprising:

initializing, using one or more computing device processors, an optimization computing model for the secure storage network, the optimization computing model being parameterized by:

a first parameter probabilistically characterizing propensity data of a collection of digital profiles associated with the secure storage network, and

a second parameter associated with a temporal window within which at least some data elements comprised in the collection of digital profiles transition from a first data state to a second data state;

determining, using the one or more computing device processors, a first dataset associated with the secure storage network, the first dataset comprising a first set of data elements, associated with the collection of digital profiles, that do not transition from the first data state to the second data state;

formatting, using the one or more computing device processors, the first dataset, thereby resulting in a training dataset for application to the optimization computing model;

applying, using the one or more computing device processors, the training dataset to the optimization computing model, thereby resulting in a trained optimization computing model;

determining, using the one or more computing device processors, a second dataset associated with the secure storage network, the second dataset comprising a second set of data elements, associated with the collection of digital profiles, that transition from the first data state to the second data state within the temporal window;

applying, using the one or more computing device processors, the second dataset to the trained optimization computing model;

in response to the applying the second dataset to the trained optimization computing model, initiating, using the one or more computing device processors, display of the optimization indicator on a first graphical display device via a first application associated with the secure storage network;

determining, using the one or more computing device processors, based on the optimization indicator, a degree or rate of transition of at least one data element of the second dataset from the first data state to the second data state within the temporal window;

determining, using the one or more computing device processors, based on the degree or rate of transition of at least one data element of the second dataset from the first data state to the second data state within the temporal window, operational data associated with one or more of the collection of digital profiles;

enabling modification of, using the one or more computing device processors, the operational data, thereby resulting in modified operational data;

transmitting the modified operational data to a computing device associated with the one or more collection of digital profiles; and

initiating, using the one or more computing device processors, transmission of the modified operational data to a second graphical display device via at least one of:

a second application associated with the secure storage network, or

a third application that is not associated with the secure storage network.

2 . The method of claim 1 , further comprising executing, using the one or more computing device processors, a computing simulation that stabilizes the optimization computing model to enable applying the second dataset to the trained optimization computing model.

3 . The method of claim 1 , wherein the optimization indicator is used to execute a computing operation to predict a rate of conversion of one or more digital profiles comprised in the collection of digital profiles from the first data state to the second data state.

4 . The method of claim 1 , wherein the optimization indicator comprises binary information associated with data elements of at least one digital profile comprised in the collection of digital profiles transitioning from the first data state to the second data state based on a configurable data object associated with the secure storage network.

5 . The method of claim 4 , wherein the modified operational data comprises content data associated with the configurable data object, the content data comprising data transmissions occurring after determining the optimization indicator.

6 . The method of claim 5 , wherein the optimization computing model is updated based on at least the optimization indicator and data element transitions of the collection of digital profiles prior to, during, or after, transmitting the content data associated with the configurable data object.

7 . The method of claim 1 , wherein optimization computing model comprises a logistic regression computing model.

8 . The method of claim 1 , wherein the first parameter comprises quantitative data based on a scale.

9 . The method of claim 1 , wherein the temporal window associated with the second parameter is at least three months.

10 . The method of claim 1 , wherein the first dataset or the second dataset comprises a plurality of properties associated with the collection of digital profiles.

11 . The method of claim 10 , wherein the plurality of properties associated with the collection of digital profiles comprise one or more of:

demographic data associated with the collection of digital profiles,

biological indication data associated with the collection of digital profiles,

one or more data protocols associated with managing the biological indication data associated with the collection of digital profiles,

response data associated with applying the one or more data protocols to the biological indication data, or

data element transition data associated with the collection of digital profiles.

12 . The method of claim 10 , wherein the plurality of properties associated with the collection of digital profiles comprise observable action data associated with the collection of digital profiles.

13 . The method of claim 1 , wherein the optimization indicator comprises at least textual or image data.

14 . A system for generating an optimization indicator based on data state transitions of data elements associated with one or more digital profiles in a secure storage network, the system comprising:

one or more hardware computing system processors; and

at least one memory storing instructions, that when executed by the one or more hardware computing system processors causes the one or more hardware computing system processors to:

initialize an optimization computing model for the secure storage network, the optimization computing model being parameterized by:

a first parameter characterizing propensity data of a collection of digital profiles associated with the secure storage network, and

a second parameter associated with a temporal window within which at least some data elements comprised in the collection of digital profiles transition from a first data state to a second data state;

determine a first dataset associated with the secure storage network, the first dataset comprising a first set of data elements, associated with the collection of digital profiles, that do not transition from the first data state to the second data state;

format the first dataset, thereby resulting in a training dataset for application to the optimization computing model;

apply the training dataset to the optimization computing model, thereby resulting in a trained optimization computing model;

determine a second dataset associated with the secure storage network, the second dataset comprising a second set of data elements, associated with the collection of digital profiles, that transition from the first data state to the second data state within the temporal window;

apply the second dataset to the trained optimization computing model;

in response to the applying the second dataset to the trained optimization computing model, initiate display of the optimization indicator on a first graphical display device via a first application associated with the secure storage network;

determine, based on the optimization indicator, a degree or rate of transition of at least one data element of the second dataset from the first data state to the second data state within the temporal window;

determine, based on the degree or rate of transition of at least one data element of the second dataset from the first data state to the second data state within the temporal window, operational data associated with one or more of the collection of digital profiles;

enable modification of the operational data, thereby resulting in modified operational data;

transmit the modified operational data to a computing device associated with the one or more collection of digital profiles; and

initiate transmission of the modified operational data to a second graphical display device via at least one of:

a second application associated with the secure storage network, or

a third application that is not associated with the secure storage network.

15 . The system of claim 14 , wherein the one or more hardware computing system processors are further configured to execute a computing simulation that stabilizes the optimization computing model to enable applying the second dataset to the trained optimization computing model.

16 . The system of claim 14 , wherein the optimization indicator is used to execute a computing operation to predict a rate of conversion of one or more digital profiles comprised in the collection of digital profiles from the first data state to the second data state.

17 . The system of claim 14 , wherein the optimization indicator comprises binary information associated with data elements of at least one digital profile comprised in the collection of digital profiles transitioning from the first data state to the second data state based on a configurable data object associated with the secure storage network.

18 . The system of claim 17 , wherein the modified operational data comprises content data associated with the configurable data object, the content data comprising data transmissions occurring after determining the optimization indicator.

19 . The system of claim 18 , wherein the optimization computing model is updated based on at least the optimization indicator and data element transitions of the collection of digital profiles prior to, during, or after, transmitting the content data associated with the configurable data object.

20 . The system of claim 14 , wherein the first dataset or the second dataset comprises a plurality of properties associated with the collection of digital profiles, the plurality of properties comprising one or more of:

demographic data associated with the collection of digital profiles,

biological indication data associated with the collection of digital profiles,

one or more data protocols associated with managing the biological indication data associated with the collection of digital profiles,

response data associated with applying the one or more data protocols to the biological indication data, or

data element transition data associated with the collection of digital profiles.